Cover Image

Explainable AI for Multivariate Time Series Pattern Exploration: Latent Space Visual Analytics with Temporal Fusion Transformer and Variational Autoencoders in Power Grid Event Diagnosis

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Xu, Haowen, Boyaci, Ali, Lian, Jianming, Wilson, Aaron
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Embodied Exploration of Latent Spaces and Explainable AI
by: Wilson, Elizabeth, et al.
Published: (2024)

Distributional Drift Adaptation with Temporal Conditional Variational Autoencoder for Multivariate Time Series Forecasting
by: He, Hui, et al.
Published: (2022)

Multivariate Variational Autoencoder
by: Yavuz, Mehmet Can
Published: (2025)

Adaptive Compression of the Latent Space in Variational Autoencoders
by: Sejnova, Gabriela, et al.
Published: (2023)

Improving Semantic Control in Discrete Latent Spaces with Transformer Quantized Variational Autoencoders
by: Zhang, Yingji, et al.
Published: (2024)

Robust Federated Learning with Confidence-Weighted Filtering and GAN-Based Completion under Noisy and Incomplete Data
by: Gokcen, Alpaslan, et al.
Published: (2025)

Grid-Orch: An LLM-Powered Orchestrator for Distribution Grid Simulation and Analytics
by: Liu, Boming, et al.
Published: (2026)

Heteroscedastic Temporal Variational Autoencoder For Irregular Time Series
by: Shukla, Satya Narayan, et al.
Published: (2021)

Uniform Transformation: Refining Latent Representation in Variational Autoencoders
by: Shi, Ye, et al.
Published: (2024)

Discrete Wavelet Transform as a Facilitator for Expressive Latent Space Representation in Variational Autoencoders in Satellite Imagery
by: Mahara, Arpan, et al.
Published: (2025)

Decoding Latent Spaces: Assessing the Interpretability of Time Series Foundation Models for Visual Analytics
by: Santamaria-Valenzuela, Inmaculada, et al.
Published: (2025)

Automating Bibliometric Analysis with Sentence Transformers and Retrieval-Augmented Generation (RAG): A Pilot Study in Semantic and Contextual Search for Customized Literature Characterization for High-Impact Urban Research
by: Xu, Haowen, et al.
Published: (2024)

A Variational Autoencoder for Neural Temporal Point Processes with Dynamic Latent Graphs
by: Yang, Sikun, et al.
Published: (2023)

MANDALA—Visual Exploration of Anomalies in Industrial Multivariate Time Series Data
by: J. Suschnigg, et al.
Published: (2025)

Latent Disentanglement in Mesh Variational Autoencoders Improves the Diagnosis of Craniofacial Syndromes and Aids Surgical Planning
by: Foti, Simone, et al.
Published: (2023)

Variational Autoencoded Multivariate Spatial Fay-Herriot Models
by: Wang, Zhenhua, et al.
Published: (2025)

VLBM: Variational Latent Basis Modeling for OOD Robust Multivariate Time Series Forecasting
by: Zhang, Xudong, et al.
Published: (2026)

Quantum Autoencoder for Multivariate Time Series Anomaly Detection
by: Tscharke, Kilian, et al.
Published: (2025)

Latent Diffusion Model without Variational Autoencoder
by: Shi, Minglei, et al.
Published: (2025)

Grammarization-Based Grasping with Deep Multi-Autoencoder Latent Space Exploration by Reinforcement Learning Agent
by: Askianakis, Leonidas
Published: (2024)

Ensemble Visualization With Variational Autoencoder
by: Wu, Cenyang, et al.
Published: (2025)

Latent Space Characterization of Autoencoder Variants
by: Shrivastava, Anika, et al.
Published: (2024)

Considering Nonstationary within Multivariate Time Series with Variational Hierarchical Transformer for Forecasting
by: Wang, Muyao, et al.
Published: (2024)

Latent Space Score-based Diffusion Model for Probabilistic Multivariate Time Series Imputation
by: Liang, Guojun, et al.
Published: (2024)

Stationarity Exploration for Multivariate Time Series Forecasting
by: Liu, Hao, et al.
Published: (2025)

LatentGandr: Visual Exploration of Generative AI Latent Space via Local Embeddings
by: Li, Mingwei, et al.
Published: (2026)

Tropical Logistic Regression Model on Space of Phylogenetic Trees
by: Aliatimis, Georgios, et al.
Published: (2023)

EventBox: A Novel Visual Encoding for Interactive Analysis of Temporal and Multivariate Attributes in Event Sequences
by: Montana, Luis, et al.
Published: (2025)

Leveraging Time Series Categorization and Temporal Fusion Transformers to Improve Cryptocurrency Price Forecasting
by: Peik, Arash, et al.
Published: (2024)

Explainable Spatio-Temporal GCNNs for Irregular Multivariate Time Series: Architecture and Application to ICU Patient Data
by: Escudero-Arnanz, Óscar, et al.
Published: (2024)

Exploring Variational Graph Autoencoders for Distribution Grid Data Generation
by: Abbas, Syed Zain, et al.
Published: (2025)

Hyperspectral Pixel Unmixing with Latent Dirichlet Variational Autoencoder
by: Mantripragada, Kiran, et al.
Published: (2022)

Enhancing Variational Autoencoders with Smooth Robust Latent Encoding
by: Lee, Hyomin, et al.
Published: (2025)

Distilling Latent Manifolds: Resolution Extrapolation by Variational Autoencoders
by: Chu, Jiaming, et al.
Published: (2026)

Negative Binomial Variational Autoencoders for Overdispersed Latent Modeling
by: Zhang, Yixuan, et al.
Published: (2025)

Latent-Compressed Variational Autoencoder for Video Diffusion Models
by: Guan, Jiarui, et al.
Published: (2026)

InvDec: Inverted Decoder for Multivariate Time Series Forecasting with Separated Temporal and Variate Modeling
by: Wang, Yuhang
Published: (2025)

VIFO: Visual Feature Empowered Multivariate Time Series Forecasting with Cross-Modal Fusion
by: Wang, Yanlong, et al.
Published: (2025)

Enclosing Prototypical Variational Autoencoder for Explainable Out-of-Distribution Detection
by: Orglmeister, Conrad, et al.
Published: (2025)

Visual Variational Autoencoder Prompt Tuning
by: Xiao, Xi, et al.
Published: (2025)